Longest Increasing Contiguous Subarray
Finds maximum length contiguous slice where elements are strictly increasing.
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Asked in interviews at
Reference implementation (Python)
def longest_increasing_subarray(arr):
max_len = curr = 1
for i in range(1, len(arr)):
if arr[i] > arr[i-1]:
curr += 1
max_len = max(max_len, curr)
else:
curr = 1
return max_lenEmbed this visualization
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<iframe src="/embed/longest-increasing-subarray" width="100%" height="380" style="border:1px solid #e6e8ec;border-radius:14px" loading="lazy" title="3D algorithm visualization by CodeWithMunnaX"></iframe>Frequently asked
What is the time and space complexity of Longest Increasing Contiguous Subarray?
Longest Increasing Contiguous Subarray runs in O(n) time and O(1) auxiliary space.
Is the Longest Increasing Contiguous Subarray visualizer free?
The core 3D visualizer, Web Audio chimes and step intuition are free. A one-time ₹49 Pro Pass unlocks advanced algorithms, large custom arrays, Battle Arena and reel export.
Which companies ask Longest Increasing Contiguous Subarray in interviews?
Longest Increasing Contiguous Subarray shows up in interviews at Netflix, Amazon, ByteDance.
How does the 3D visualization of Longest Increasing Contiguous Subarray work?
Each array value becomes a 3D pillar whose height maps to its value. Comparisons glow amber, swaps flash red, and settled elements lock green while a floating pointer badge tracks the active index — synchronized line-by-line with the Python code.